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This article explains Truncated SVD and its relation to PCA, demonstrating how it can be used to approximate images by reconstructing them with fewer singular values. It uses the example of a moon image to illustrate the reconstruction process.
This paper introduces drXAI, a method that uses XAI attribution to reduce data size for time series classification, achieving 80-90% data reduction while maintaining accuracy, enabling large models to scale.
This paper applies Random Forest Recursive Feature Elimination to Nigerian household survey data to identify minimal predictors that accurately classify poverty status, quintile distribution, and inequality position, showing that machine learning can reduce data requirements while preserving distributional information for monitoring poverty and inequality.